I’m building a microservices app and need tracing from day one

Great idea—adding tracing from day one is much easier than retrofitting it later.

Here’s a practical approach for a microservices app:

1) Use OpenTelemetry as the standard

OpenTelemetry (OTel) is the current best default for:

• Traces
• Metrics
• Logs (optional, but useful)

Why:

• Vendor-neutral
• Works across many languages/frameworks
• Easy to export to Jaeger, Grafana Tempo, Datadog, New Relic, etc.

2) Standardize trace context propagation

Make sure every service:

• Accepts incoming trace context
• Injects outgoing trace context

Use W3C Trace Context headers:

• traceparent
• tracestate

This ensures a request can be followed across all services.

3) Instrument at the boundaries first

Start with:

• HTTP/gRPC server middleware
• HTTP/gRPC client middleware
• Message queue producers/consumers
• Database calls
• External API calls

This gives you most of the value immediately with minimal effort.

4) Pick a backend early

Choose where traces will go:

• Jaeger: simple, popular for self-hosting
• Grafana Tempo: great if you already use Grafana
• Vendor APM: if you want managed observability

A common setup:

• App services → OpenTelemetry Collector → tracing backend

5) Add an OpenTelemetry Collector

This is strongly recommended. It acts as a buffer and routing layer.

Benefits:

• Central place to batch, retry, and filter telemetry
• Can export to multiple backends
• Reduces coupling between app and observability vendor

6) Correlate traces with logs and metrics

Make sure logs include:

• trace_id
• span_id

This makes debugging much easier when a trace shows an error and you need log details.

7) Keep naming conventions consistent

Use clear span names like:

• GET /orders/{id}
• POST /payments
• Kafka publish orders.created
• SQL SELECT orders by id

Also add useful attributes:

• service.name
• deployment.environment
• http.method
• http.route
• db.system
• messaging.system

8) Be careful with sampling

For dev/test:

• Sample everything

For production:

• Use head sampling or tail sampling depending on volume
• Consider keeping all error traces
• Tail sampling via collector is often useful for microservices

9) Propagate baggage sparingly

If you need extra request-scoped metadata, use OTel baggage carefully. Don’t put sensitive data there.

10) Build a “golden path”

Create reusable instrumentation libraries or middleware so every service starts with:

• trace propagation
• standard spans
• log correlation
• exporter config

This prevents each team from doing it differently.

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Recommended minimal architecture

Service code
→ OpenTelemetry SDK/instrumentation
→ OpenTelemetry Collector
→ Jaeger / Tempo / APM backend
→ UI for trace inspection

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If you want the simplest possible starting plan

1. Add OpenTelemetry SDK to each service
2. Enable auto-instrumentation where possible
3. Propagate W3C trace headers
4. Send data to an OpenTelemetry Collector
5. Export to Jaeger or Tempo
6. Add trace_id to logs

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A few common pitfalls

• Not propagating context between services
• Sampling too aggressively too early
• Mixing incompatible tracing standards
• Forgetting async/message queue tracing
• Sending sensitive user data in span attributes

If you want, I can also give you:

1. a recommended stack for your language/runtime, or
2. a step-by-step implementation plan for tracing in microservices.